This projects investigates accidents locations, participants and road types. Visualisations give intuitive insights about the data and mediate the data's main characteristics. The question that is tried to be answered is whether there are areas with safety vulnerabilities.
Sidenote: In case you are viewing this as a PDF please note that some plots in this notebook are interactive and this can only experienced when downloading the .ipynb file.
The following code assumes that the data was loaded into the database using the data engineering pipeline.
This process can be initiated using the file launcher.py. There are about 1.1 Million records in the database.

The explorer class provides methods that directly yield vizualisation plots. The internal data selection is mainly based on SQL queries.
import os
os.chdir('project')
from project.Explorer import Explorer
explorer = Explorer()
On the following map one can see the location of accidents. Their color coding indicates the type of road they took place on. Note that not all accidents are displayed, because that can lead to a severe lagging of the notebook due to the high number of data points in the interactive plot.
This is the explanation of the most common road type names:
explorer.plot_accident_location(n_accidents=500000)